Position: AWS Data Engineer

Experience: 3-5 Years

Location: Chennai, Bangalore

Key Skills: AWS Data Engineering, Python, Lambda

About The Role

We're looking for an experienced AWS Data Engineer to join a fast-paced data engineering team building scalable data solutions for our customers. In this role, you'll own the technical design, implementation, optimization, and maintenance of data engineering components — working across data warehouse, data lake, and lakehouse architectures on AWS. This is a hands-on role for someone who enjoys solving complex data problems and wants to work with modern cloud-native tooling.

Roles & Responsibilities

Design, build, and maintain robust data pipelines across AWS data warehouse, data lake, and lakehouse environments.
Develop and optimize batch and streaming pipelines using PySpark / Spark Scala for near real-time analytics.
Build and orchestrate workflows using AWS services such as Glue, Lambda, Step Functions, Redshift, EMR, and Kinesis.
Write and tune complex SQL queries, focusing on performance and scalability.




Apply data governance best practices across data platforms and analytical solutions.
Collaborate with cross-functional teams to translate business requirements into reliable, production-ready data solutions.
Contribute to CI/CD pipelines and DevOps practices for data engineering components, using Git for version control.

Profile Requirements

3–5 years of hands-on experience designing, developing, and implementing data engineering solutions.
Robust SQL development skills, including query optimization and performance tuning.
Solid programming experience with Python.
Proven experience building data pipelines with PySpark or Spark Scala, including streaming pipelines for near real-time use cases.
Hands-on experience with AWS data engineering services — Glue, Lambda, Step Functions, Redshift, EMR, Kinesis, or similar.
Working experience with at least one NoSQL database.
Good grasp of modern data architecture patterns

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